Table 4 Summary of included articles’ study design, context, method of identifying brokers and key findings about brokers

Ahuja, G. (2000) [34]

1. Interorganisational

Nonredundant contacts per total contacts

Firm collaborations within the international chemicals industry

Brokering structural holes between companies increases innovative output up to a point before it decreases.

2. Longitudinal, retrospective

3. Documentary data

4. Regression analyses

Aral, S. & Van Alstyne, M. (2011) [35]

1. Interpersonal

Network constraint

Employees from a US executive recruiting firm

Brokers’ success at accessing novelty depends on their knowledge environment.

2. Cross-sectional

3. Analysis of email content

4. SNA, word mining

Balkundi, P., Barsness, Z. et al. (2009) [36]

1. Interpersonal

Betweenness centrality

19 teams from across two US paper and wood-based building product plants

Leaders who were brokers (high betweenness centrality) in the advice-seeking network had teams with higher team conflict and lower viability.

2. Cross-sectional

3. Paper-based survey using roster

4. SNA

Bercovitz, J. & Feldman, M. (2011) [37]

1. Interpersonal

Measure of "expertise distance" between academic departments; number of ties to external networks

Academic research teams from two US universities

Costs are involved in coordinating diverse teams but such teams are more successful inventors.

2. Cross-sectional

3. Documentary data: invention disclosures, personnel records, patents

4. PROBIT modelling

Burt, R. (2004) [12]

1. Interpersonal

Network constraint

US electronics company managers

Brokers accrue social capital by being able to see and express more “good ideas.”

2. Longitudinal, retrospective

3. Online survey; archival data

4. SNA; regression analyses

Colazo, J. (2010) [38]

1. Interteam

Boundary-spanning activity (number of team members who work on another project per number of members in focal team)

Open source software development teams

Boundary spanning activity in teams was positively associated with quality but negatively associated with productivity.

2. Longitudinal, retrospective

3. Archival data on teams and project quality

4. SNA, regression analyses

Creswick, N. & Westbrook, J. (2010) [39]

1. Interpersonal

Betweenness centrality

Communication between ward staff of an Australian teaching hospital

SNA can identify strategic people that act as brokers.

2. Case study

3. Paper-based survey using roster

4. SNA

Cummings, J. & Cross, R. (2003) [25]

1. Interpersonal

Effective size

182 work groups (average 8 members) in a US Fortune 500 telecommunication firm

Leaders who act as brokers ("go-betweens") within teams can cause a bottleneck in information flow that can decrease productivity.

2. Cross sectional

3. Email survey using roster

4. Regression analyses

Di Marco, M., Taylor, J. et al. (2010) [28]

1. Interpersonal

Betweenness centrality

Indian and US post-graduate students in two engineering project teams

Nominated cultural boundary spanner (CBS) can decrease cultural based knowledge system conflicts and trigger emergent CBS.

2. Ethnographic

3. Observation over 3 days

4. SNA

Fleming, L., Mingo, S. et al. (2005) [40]

1. Interpersonal

External ties (ln)

35,400 inventors across 16 East German regional innovation networks

Brokers can generate innovative ideas but their presence can hamper its diffusion and use.

2. Longitudinal, retrospective

3. Archival patent data

4. Regression analyses

Hanson, D., J. Hanson, et al. (2008) [41]

1. Interpersonal

Betweenness centrality

152 members of an Australian network of community groups for safety promotion

Asymmetric distribution of influence: six members with high centrality and betweenness centrality.

2. Longitudinal case study, prospective

3. Paper-based survey; 3 initial waves of snowballing to identify members

4. SNA

Hargadon, A. & Sutton, R. (1997) [42]

1. Interpersonal

Observation

Design engineers at IDEO, a US product design firm

Technology brokering involves four stages: access, acquisition, storage and retrieval.

2. Ethnographic

3. Observation, interviews

4. Grounded theory

Hawe, P. and L. Ghali (2008) [43]

1. Interpersonal

Betweenness centrality

Staff and teachers at a Canadian high school

SNA useful tool to identify people of strategic influence (including brokers) in health promotion activities.

2. Case study

3. Paper-based survey using roster

4. SNA

Heng, H. K., W. D. McGeorge, et al. (2005) [44]

1. Interpersonal

Betweenness centrality; effective size and efficiency (SH)

Department managers of an Australian hospital

Facility manager had high brokerage potential.

2. Case study

3. Survey using name generator

4. SNA

Lingo, E. & O'Mahony, S. (2010) [29]

1. Interpersonal

Observation; assessment of tertius orientation (tertius gaudens or tertius iungens)

Independent music producers in the Nashville (US) country music industry

Brokerage is a process (cf. position) and both tertius orientations can be used to produce collective outcomes.

2. Ethnographic

3. Observation, interviews

4. Grounded theory

Luo, J.-D. (2005) [26]

1. Interpersonal

Betweenness centrality

296 workers in two multinational technology companies in mainland China and in Taiwan

Brokers ("go-betweens") in advice-seeking networks have informal power and are higher in particularist trust than others.

2. Cross-sectional

3. Survey

4. Regression analyses

Marrone, J., Tesluk, P. & Carson, J (2007) [45]

1. Interpersonal

Self- and alter-assessment

190 MBA students in 31 teams in a US university consulting project

Team level boundary spanning mitigates the negative cost of individual boundary spanning.

2. Cross-sectional

3. Survey

4. Hierarchical linear modelling (individuals nested within teams)

Obstfeld, D. (2005) [30]

1. Interpersonal

Constraint; tertius iungens orientation

Designers, engineers and managers in a US engineering division of automotive manufacturer

Tertius iungens orientation, social knowledge and network density are independent predictors of involvement in innovation.

2. Ethnography, case study

3. Email survey using name generator, interviews, observation

4. Qualitative, regression analyses

Padula, G. (2008) [46]

1. Interorganisational

"Shortcuts:" number of cumulative alliances to other clusters

US mobile phone firms

Network cohesion and brokerage ("shortcuts") synergise to produce best environment to generate and produce innovation.

2. Longitudinal, retrospective

3. Archival patent data

4. Regression analyses

Rangachari, P. (2008) [47]

1. Interpersonal

Between subgroups in structural equivalence analysis

Administrators and professional staff from four hospitals in New York State

Brokerage across professional subgroups results in better coding performance.

3. On-line survey using roster; interviews

4. SNA; structural equivalence analyses

2. Cross-sectional

Rodan, S. & Galunic, C. (2004) [48]

1. Interpersonal

Network sparseness = 1-Density

Managers from a Scandinavian telecommunications company

Access to heterogeneous knowledge may be more important than sparse network structures for innovative managerial performance.

2. Cross-sectional

3. Paper-based surveys using roster and one wave of snowballing to include named external contacts

4. Regression analyses

Soda, G., A. Usai, et al. (2004) [49]/ Zaheer, A. and G. Soda (2009) [50]

1. Interpersonal then aggregated to team level

Network constraint

TV production specialist teams from Italy

Current brokerage associated with higher team performance. Past brokerage ties are not as effective as current ones.

2. Longitudinal, retrospective

3. Archival data on 501 TV

productions

4. SNA, regression analyses

Susskind, A., P. Odom-Reed, et al. (2011) [51]

1. Interpersonal

Network constraint, effective size, efficiency and hierarchy

Members of 11 hospitality management programs across six hotels and 11 US universities

Level of brokerage was not significantly related to individual team member performance but negatively related to overall team performance.

4. SNA, regression analyses2. Cross-sectional

3. Survey using roster

Tiwana, A. (2008) [52]

1. Interpersonal

"Bridging ties" extent of heterogeneity of expertise, background and skills of fellow team members

173 team members within a US internet business applications company

Both strong ties and brokerage (“bridging”) ties are needed to realise knowledge integration.

2. Cross-sectional

3. Survey

4. Regression analyses